Cycle-Accurate Debugging of Embedded Designs Using Recurrent Neural Networks

摘要

This research work presents a methodology for debugging embedded designs by using recurrent neural networks. In this methodology, a cycle-accurate lossless debugging system with unlimited trace window is used for debugging. The lossless trace resembles a time data series. A recurrent neural network trained either through a golden reference or from the actual time series can be used to predict the incoming debugging data. A bug can be easily isolated based upon the discrepancy between the received and the predicted time series. This allows to draw conclusions to speed up the debugging process.